Metric details with threshold from accuracy metric
score
threshold
logloss
0.218947
nan
auc
0.945282
nan
f1
0.944106
0.518876
accuracy
0.908639
0.518876
precision
0.928183
0.518876
recall
0.960586
0.518876
mcc
0.697582
0.518876
Confusion matrix (at threshold=0.518876)
Predicted as Major
Predicted as Minor
Labeled as Major
606
264
Labeled as Minor
140
3412
Learning curves
Decision Tree
Tree #1
Rules
if (APR Severity of Illness Code <= 2.5) and (Age Group <= 3.5) and (APR MDC Code > 0.5) then class: Minor (proba: 99.42%) | based on 7,536 samples
if (APR Severity of Illness Code > 2.5) and (APR Severity of Illness Description > 0.5) and (Age Group <= 3.5) then class: Minor (proba: 66.39%) | based on 1,693 samples
if (APR Severity of Illness Code <= 2.5) and (Age Group > 3.5) and (APR Severity of Illness Code > 1.5) then class: Minor (proba: 82.97%) | based on 1,374 samples
if (APR Severity of Illness Code > 2.5) and (APR Severity of Illness Description > 0.5) and (Age Group > 3.5) then class: Major (proba: 73.79%) | based on 1,339 samples
if (APR Severity of Illness Code > 2.5) and (APR Severity of Illness Description <= 0.5) and (CCS Diagnosis Code <= 253.5) then class: Major (proba: 95.64%) | based on 780 samples
if (APR Severity of Illness Code <= 2.5) and (Age Group > 3.5) and (APR Severity of Illness Code <= 1.5) then class: Minor (proba: 97.49%) | based on 517 samples
if (APR Severity of Illness Code > 2.5) and (APR Severity of Illness Description <= 0.5) and (CCS Diagnosis Code > 253.5) then class: Major (proba: 64.0%) | based on 25 samples
if (APR Severity of Illness Code <= 2.5) and (Age Group <= 3.5) and (APR MDC Code <= 0.5) then class: Major (proba: 100.0%) | based on 1 samples